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Commercial wind turbines modeling using single and composite cumulative probability density functions

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Název: Commercial wind turbines modeling using single and composite cumulative probability density functions
Autoři: Othman A. M. Omar, Hamdy M. Ahmed, Reda A. Elbarkouky
Informace o vydavateli: Zenodo
Rok vydání: 2021
Sbírka: Zenodo
Témata: Cumulative probability density functions, Mathematical modelling, Power curves, Wind turbines
Popis: As wind turbines more widely used with newer manufactured types and larger electrical power scales, a brief mathematical modelling for these wind turbines operating power curves is needed for optimal site matching selections. In this paper, 24 commercial wind turbines with different ratings and different manufactures are modelled using single cumulative probability density functions modelling equations. A new mean of a composite cumulative probability density function is used for better modelling accuracy. Invasive weed optimization algorithm is used to estimate different models designing parameters. The best cumulative density function model for each wind turbine is reached through comparing the RMSE of each model. Results showed that Weibull-Gamma composite is the best modelling technique for 37.5% of the reached results.
Druh dokumentu: article in journal/newspaper
Jazyk: unknown
Relation: https://zenodo.org/records/4629323; oai:zenodo.org:4629323
DOI: 10.11591/ijece.v11i1.pp47-56
Dostupnost: https://doi.org/10.11591/ijece.v11i1.pp47-56
https://zenodo.org/records/4629323
Rights: Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
Přístupové číslo: edsbas.FC135690
Databáze: BASE
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  – Url: https://doi.org/10.11591/ijece.v11i1.pp47-56#
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PubType: Academic Journal
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IllustrationInfo
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  Label: Title
  Group: Ti
  Data: Commercial wind turbines modeling using single and composite cumulative probability density functions
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  Data: <searchLink fieldCode="AR" term="%22Othman+A%2E+M%2E+Omar%22">Othman A. M. Omar</searchLink><br /><searchLink fieldCode="AR" term="%22Hamdy+M%2E+Ahmed%22">Hamdy M. Ahmed</searchLink><br /><searchLink fieldCode="AR" term="%22Reda+A%2E+Elbarkouky%22">Reda A. Elbarkouky</searchLink>
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  Data: Zenodo
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  Label: Publication Year
  Group: Date
  Data: 2021
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  Data: <searchLink fieldCode="DE" term="%22Cumulative+probability+density+functions%22">Cumulative probability density functions</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+modelling%22">Mathematical modelling</searchLink><br /><searchLink fieldCode="DE" term="%22Power+curves%22">Power curves</searchLink><br /><searchLink fieldCode="DE" term="%22Wind+turbines%22">Wind turbines</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: As wind turbines more widely used with newer manufactured types and larger electrical power scales, a brief mathematical modelling for these wind turbines operating power curves is needed for optimal site matching selections. In this paper, 24 commercial wind turbines with different ratings and different manufactures are modelled using single cumulative probability density functions modelling equations. A new mean of a composite cumulative probability density function is used for better modelling accuracy. Invasive weed optimization algorithm is used to estimate different models designing parameters. The best cumulative density function model for each wind turbine is reached through comparing the RMSE of each model. Results showed that Weibull-Gamma composite is the best modelling technique for 37.5% of the reached results.
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  Data: 10.11591/ijece.v11i1.pp47-56
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  Data: Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
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      – SubjectFull: Cumulative probability density functions
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      – SubjectFull: Mathematical modelling
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      – SubjectFull: Power curves
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